Atrial fibrillation and atrial flutter are types of cardiac arrhythmia (hereinafter, collectively referred to as “AF”) or abnormal heart rhythm that are difficult to automatically identify. The difference between atrial fibrillation and atrial flutter is mainly one of atrial rate, atrial flutter being the faster of the two.
By way of background, FIG. 1 illustrates a typical electrocardiogram (ECG) tracing of a normal heartbeat (or cardiac cycle), showing the electrical conduction system of the heart. In cardiac practice, heartbeats are named according to the initial source of the heartbeat. The normal beating of the heart is known as “sinus rhythm”, because the normal heart beat is initiated by a small area of specialized muscle in the atria referred to as the sinoatrial (SA) node (or more commonly, the “sinus node”). When electrical activity is spontaneously generated by the sinus node, the electrical impulse is propagated throughout both the right atrium and left atrium, stimulating the myocardium of the atria to contract. When the atria contract, blood is pumped from the atria of the heart to the lungs and then back into the ventricles.
Referring now to FIG. 1, the conduction of the electrical impulse throughout the atria is seen on the ECG as P-wave 101. Thus, the P-wave 101 represents the electrical potential generated by atrial muscle cell depolarization as the heart's atrial chambers contract.
The spread of electrical activity through the ventricular myocardium causes the ventricles of the heart to contract. When the ventricles contract, the blood in the ventricles is pumped at high pressure around the body (and eventually back to the atria). The conduction of the electrical impulse throughout the ventricles is seen on the ECG as the QRS complex 102 on the ECG. More specifically, the QRS complex 102 represents the electrical potential generated by ventricular muscle cell depolarization as the heart's ventricular chambers contract.
The “AV node” is a specialized section of the myocardium located between the atria and the ventricles. The AV node functions as a critical delay in the conduction system. In order for the heart to work well, the heart must first pump blood from the atria to the ventricles (via the lungs, where the blood becomes oxygenated). Once this occurs, the ventricles then pump the oxygenated blood throughout the body. The AV delay allows the atria to fill the ventricles with blood before the ventricles are pumped. If the ventricles are pumped prior to being filled with blood from the lungs via the atria, the ventricular pump action would oppose the movement of blood from atria to ventricles and reduce the pressure of the blood moving from the ventricles to the rest of the body. The delay in the AV node is observed as the PR segment 105 on the ECG.
The last event of the cycle is the repolarization of the ventricles, represented on the ECG by T-wave 103. The T-wave 103 represents the electrical potential generated as the ventricles of the heart recover (or repolarize) from a state of depolarization after the QRS complex has occurred. It should be noted that there is an equivalent repolarization wave for the P-wave, occurring during the PR segment and traversing somewhat into the QRS complex: however, from a surface ECG, this repolarization signal is typically too small to be seen.
Other characteristic features of sinus rhythm include a PR-interval 104, ST-segment 106 and QT-interval 107. The PR-interval 104 is measured from the beginning of the P-wave 101 to the beginning of the QRS complex 102. The ST-segment 106 is measured from the end of the QRS complex 102 to the beginning of the T-wave 103. The QT-interval 107 is measured from the beginning of the QRS complex 102 to the end of the T-wave 103. These generic features of sinus rhythm serve as hallmarks for comparison with normal ECGs.
FIG. 2 illustrates two successive cycles of sinus rhythm. The distance between the R waves of two successive cardiac cycles 200 is known as the RR interval 201. While one would ideally measure the ‘ventricular rate’ as the QQ interval 202 (which is the interval from QRS onset to the next QRS onset), in practice, the RR interval is used as the measurement of ventricular rate, due to the practical difficulty of reliably measuring the small, inconsistently sized and inconsistantly occurring Q-wave. In the case of sinus rhythm, when successive beats are both “Normal”, the RR interval of such a cycle is often referred to as an “NN interval”. The NN interval 203 thus reflects the underlying sinus rhythm. The distance between the on-set of successive P waves is known as the PP interval (or atrial rate) 204.
As shown in FIGS. 1 and 2, the five distinct waves (P, Q, R, S and T) present in a single beat of the heart in sinus rhythm, along with the characteristic segments and intervals (such as PR, ST, QT, and RR) between two cardiac cycles, all occur in a specific order with an expected range of relative sizes. While there is a significant range within which variations in rhythm are considered normal, anything that deviates from sinus rhythm by more than a certain amount may be indicative of a heart condition.
As mentioned above, the normal beating of the heart is known as “sinus rhythm”. When areas of the heart other than the sinus node initiate a heartbeat, they are generally referred to as “ectopic beats” since they occur ‘out-of-place’ with respect to sinus rhythm. More specifically, ectopics are named according to the area of the heart (or focus) that initiated the heartbeat, and often have subsidiary information regarding whether these heartbeats are at a notably different heartrate to that of the current sinus rate or not. For example a heartbeat having an atrial origin, excluding the sinus node, may be referred to as an “atrial ectopic”. Were this heartbeat to occur faster than the current sinus rate, it would be termed a “premature atrial ectopic”; were it to occur slower than the current sinus rate, it would be termed an “atrial escape beat”.
Similarly, for ventricular activity, the terms “ventricular ectopics”, “premature ventricular ectopics” (or “complexes”, thus often called “PVCs”), and “ventricular escape beats” are used.
Even the aforementioned AV node can initiate heartbeats—referred to as junctional ectopics—though it is usual practice to group these together with atrial ectopics under the umbrella-name “supra-ventricular ectopics” or SVEs (so called as the atria and AV node are both physically ‘above’ the ventricals).
It should be noted that almost any area of the heart can generate a heartbeat as a back-up mechanism for when the sinus node does not start a heartbeat when it should. Escape ectopics are a manifestation of the back-up mechanism working correctly and are thus not themselves a problem but rather indicate that a problem has occurred with the sinus node. However, premature ectopics occur before the sinus node and override the correct sinus beat, thus indicating a problem with the area of the heart that prematurely generated an ‘erroneous’ back-up beat.
Most people spend most of their time in sinus rhythm, with some infrequent ectopics occurring. When ectopics become frequent, it is usually caused by a specific part of the heart causing a problem. For example, a specific area of the heart may be implicated if a particular premature SVE or PVC becomes common, sometimes occurring in lengthy patterns such as ventricular bigeminy (such as where a sinus beat is followed by a PVC and this pattern then repeats over and over).
Atrial fibrillation and atrial flutter are related types of cardiac arrhythmia (or abnormal heart rhythm) where rather than just a specific problem area of the heart causing a specific type of ectopic, the entire atria starts to generate electrical impulses that can initiate a heartbeat. In a sense, AF is effectively caused by hundreds of different atrial ectopics, all in competition with each other, overwhelming the sinus node. Because the area of the heart that generates the next heartbeat is not fixed, the heart rate of the next heartbeat is also not fixed and thus a highly chaotic sequence of heartbeats is observed. In addition, several P-waves per QRS complex are observed, as the ventricles cannot respond to every P-wave the atria generate. As the P-waves originate from different parts of the atria, their shapes are not constant, so the collection of high-rate P-waves between QRS complexes in AF can often resemble little more than a messy line on an ECG. Thus, in AF, the electrical impulses that are normally generated by the SA node are replaced by disorganized activity in the atria. In the case of atrial flutter, some level of organization can sometimes occur in the atria, with the multiple-P-waves starting to look like a train of “saw-tooth” waves at a very high atrial rate.
There are instances of AF however, where the ventricular rate is not chaotic. This happens for one of two reasons: either the ventricular rate has reached the maximum possible rate and thus, responds to whatever random P-wave that occurs at a time which allows it to continue at this rate, or very rarely, “AV dissociation” occurs, where the communication between the atria and the ventricles has completely broken down and which typically requires pacemaker implantation.
Prior art methods have attempted to detect AF events based on either the variability of ventricular rate and/or measurements of the atrial rate. However, conventional prior art methods for detecting AF using measurements of atrial rate are lacking, in that atrial rate is a difficult parameter to measure due to the small size of P-waves and their inconstant morphology during AF events. Typically, only internal pacemaker or ICD devices attempt to measure atrial rate, using a sensor that is physically attached to the atrium in order to achieve this. Other methods for atrial rate determination are notoriously unreliable in an ambulatory setting, and are thus rarely attempted.
Further, while there is a significant amount of prior art relating to methods for detecting AF, they all tend to suffer the same problem, specifically, that commonly occurring non-AF arrhythmia is mistaken for AF by the detection method.
Specifically, in prior art methods for detecting AF that are based on RR variability measurements, false positive AF detections are often caused by non-AF ectopics as these also cause significant RR variability. Much of the prior art assumes that non-AF ectopics do not occur over long durations of time. However, this is not the case for certain patterns of ectopics, such as atrial bigeminy, ventricular bigeminy or intermittent heart block, which can and do occur for extended periods of time.
For example, Hewlett Packard Labs (HPL) has developed a method for detection of atrial fibrillation for a long-term telemonitoring system. (Computers in Cardiology 2005; 32:619-622). In particular, HPL presents a “method to automatically detect Atrial Fibrillation (AF) for ambulatory monitoring . . . [with an] approach based on the variance of R-R intervals . . . ” More specifically, the HPL method “uses the morphology-independent QRS detector wqrs to compute R-R intervals and variance and then smooth the resulting classifications for further robustness.” This system, however, effectively treats all long-term non-sinus behavior as atrial fibrillation and thus fails to take into consideration long-term confounding events. It is also limited to detecting AF events having a duration of two minutes or longer.
U.S. Pat. No. 6,871,089 (the “'089 patent”), assigned to Card Guard Technologies, Inc., describes “a method of detecting atrial fibrillation in a patient, the method comprising: measuring R-R intervals between a plurality of QRS complexes of the patient, including present and preceding QRS complexes; forming a first ratio by dividing an R-R interval into another R-R interval in which one R-R interval is the present interval and one R-R interval is a preceding interval; forming a second ratio by dividing an R-R interval into another R-R interval in which one R-R interval is the present interval and one R-R interval is a preceding interval different from the preceding interval used in the first ratio; averaging a plurality of first ratios to form a first average; averaging a plurality of second ratios to form a second average; analyzing the difference between the first and second averages; [and] comparing the difference between the averages to a threshold to determine if an atrial fibrillation exists in the patient.” Thus, the '089 patent calculates ratios of the current R-R interval to previous R-R intervals and compares those ratios to a validating threshold. This method is targeted towards avoiding variability caused by PVCs, bigeminy and trigeminy, however, adversely impacts the variability measurement within true AF, which on a short time-scale (the two or three intervals as described in this patent) will often exhibit interval changes similar to such arrhythmia, and can thus be similarly suppressed.
In another example, United States Patent Publication Number 2006/0084883, assigned to the University of Washington, discloses “a method for detection of an arrhythmia, the method comprising: determining number of heart beat intervals; determining an instantaneous heart rate for each of the heart beat intervals; determining the variability of the instantaneous heart rates compared to a mean of the number of instantaneous heart rates; determining a non-linear value that represents the variability of the instantaneous heart rates; and detecting the arrhythmia by comparing the non-linear value with a predetermined threshold.” Specifically, the disclosed methods “are based on the variability of RR intervals.” The methods of the patent application disclosed herein do aim to exclude some ectopy by applying non-linear filtering to the sequence of successive differences of RR intervals. However, filtering the differences between successive RR intervals assumes that there are some intervals that can be valid indicators of non-ectopic transition intervals. For arrhythmia such as bigeminy, this assumption is not correct and this method will measure high variability, and thus detect AF, where such confounding arrhythmia is present. Thus, the method can only detect isolated non-AF arrhythmia—longer-term patterns of ectopic states, such as bigeminy or intermittent heart block, will inevitably cause false positive AF detection.
U.S. Pat. No. 6,490,479, assigned to GE Medical Systems Information Technologies, Inc., describes “a method of detecting an arrhythmia from ECG information, the method comprising: classifying the ECG information; determining intervals between recurring events in the ECG information; determining a probability that an irregular condition exists based on classifying the ECG information and determining an interval between recurring events; generating a state variable based upon the determined probability; generating a contextual output based on similarities in intervals between recurring events; determining the presence of a P-wave in the ECG information; generating a detection output based on determining the presence of a P wave; and determining the existence of the irregular condition based on the state variable, the contextual output, and the detection output.” The system and method described relies upon reliable P-wave detection, a process that is notoriously unreliable when performing non-invasive heart monitoring as described above.
U.S. Pat. No. 6,519,490, (the “'490 patent”) assigned to Wiesel, describes “a method of detecting irregular cardiac activity, said method comprising the steps of (a) determining a plurality of time intervals each corresponding to a respective time period between successive ones of a sequence of heartbeats; (b) determining a mean and a standard deviation of said plurality of time intervals; (c) selecting, when a quotient formed by dividing said standard deviation by said mean has a value greater than or equal to a threshold value, a shortest one of said plurality of time intervals and a succeeding time interval that immediately follows said shortest one; (d) determining, when said succeeding time interval has a value less than or equal to said mean, that said cardiac activity is irregular.” The '490 patent effectively locates regions of the heartbeat signal that have irregularity, then performs a simple check if the irregularity is caused by an isolated PVC or SVE: if so, it is excluded, if not, an “irregular heart rate” is detected, which can be loosely associated with AF. Thus, the '490 patent does not specifically detect AF, but rather “irregular heart rate” regions. Similarly, U.S. Pat. No. 7,020,514, also assigned to Wiesel, does not differentiate the different types of irregular heartbeats and only determines a pulse rate pattern that indicates a possible AF event.
In addition, other prior art conventional methods of analyzing RR interval patterns to detect AF events art are illustrated in the following United States Patents. Specifically, U.S. Pat. No. 6,922,584 describes a method wherein RR variability is essentially compared to a heart-rate-dependant threshold to detect AF. Further, U.S. Pat. No. 7,031,765 is directed towards clustering analyses of RR interval (or ΔRR interval) scatter plots, which require a significant number of values to create, and is thus limited to detecting long AF events only. Still further, U.S. Pat. No. 7,120,485 (and similarly, U.S. Pat. No. 7,146,206) describes a method that uses ΔRR histograms and compares the histograms to a set of pre-generated template AF histograms to identify AF, requiring a significant number of values to build reliable histograms and thus is limited to detecting long AF events only. U.S. Pat. No. 7,194,300 uses a technique where certain thresholds of RR variability are pre-determined, and only RR variability between these thresholds (i.e. neither very low, nor very high) is considered ‘relevant’ to AF, with other variability being deemed to be characteristic of non-AF behavior. Thus, AF events are defined over regions where some weighting function of each RR interval's relevance (or lack thereof) meets some defined criteria.
U.S. Pat. No. 6,597,943, assigned to GE Medical Systems Information technologies, discloses “a method and apparatus for differentiating among atrial-flutter, atrial-fibrillation and other cardiac rhythms [that] includes the steps of estimating spectral entropy of atrial cardiac activity from an electrocardiogram of a patient and determining that the patient has atrial fibrillation when the spectral entropy is greater than a predetermined value. The method involves determining an average temporal distance between successive R-waves identified within the QRS complex of the heartbeat of the patient over the sampling interval; forming a template of the QRS complex and T-wave by averaging respective sample values ahead of and behind the identified R-wave.” This method is directed towards removing the QRS and T-wave from the ECG signal, and then performing an analysis on the remaining atrial ECG signal. Due to the low signal strength of P-waves and the irregularity of QRS and T-waves, this method requires high quality, low noise ECG signals and is not well suited to ambulatory measurement where QRS and T-wave variability is significantly increased with respect to resting ECG measurements.
As discussed above, conventional prior art techniques take advantage of high RR variability to detect AF. However, most non-AF types of heart arrhythmia also generate high RR variability and thus, confound the use of high RR variability as a means to detect AF.
More specifically, the prior art based on RR variability uses a direct analysis of the variability of sequential RR intervals, thus assuming that in the sequence of RR intervals, there exists some RR variability that is not dominated by non-AF ectopy. However, for longer-term patterns of ectopic states, such as atrial bigeminy, ventricular bigeminy or intermittent heart block, which can and do occur for extended periods of time, this assumption is not the case and false positive AF detections will result.
What is therefore needed is a method for detecting AF events that advantageously analyzes the RR interval states rather than a sequence of RR interval differences.
What is also needed is a method for detecting AF events that obtains a high variability measurement for AF but does not suffer a high measurement for the confounding ECG abnormality case.